GR-MG

Reported on 2 benchmarks across 2 tasks · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Robots1 result

Robot ManipulationonCALVIN
avg. sequence length (D to D)· 2024-08-26
4.04
best: 4.44 (DreamVLA)
SOTA
GR-MG: Leveraging Partially Annotated Data via Multi-Modal Goal-Conditioned Policy arXiv:2408.14368

Methodology1 result

Zero-shot GeneralizationonCALVIN
Avg. sequence length· uses extra data· 2024-08-26
4.04
SOTA
GR-MG: Leveraging Partially Annotated Data via Multi-Modal Goal-Conditioned Policy arXiv:2408.14368